In the Wired World, Feeds Drive Trading

When the words "explosions" and "White House" popped up Tuesday on a verified Associated Press Twitter account, computers in the bare-bones offices of a New York City startup sprang into action.

The computers, housed in the Madison Avenue headquarters of a company called Dataminr, sent alerts to clients like hedge funds and government agencies about the apparent news. Shortly thereafter, the Dow Jones Industrial Average tumbled 145 points in seconds.

But the machines weren't fooled: Before the AP announced that the tweet was a hoax—its account had been hacked—Dataminr's computers generated a fresh alert saying the news may not be legitimate.

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Moments later, shares rebounded across the board, and the blue-chip index ended the day with gains greater than before the incident.

Tuesday's tumult is shining a light on the investment world's use of sophisticated computers programmed to scan news streams—including those from Twitter and other social media—to make buy or sell decisions in fractions of an instant.

The technology has been around for several years, but it is increasingly finding adherents among financial firms, including hedge funds, investment banks and even long-term investors such as mutual-fund companies. Experts say traders use the data for just about every kind of investment around the world, from U.S. stocks to the Korean won.

To some on Wall Street, the Securities and Exchange Commission's recent decision to allow companies to release material information via Twitter had "legitimized" the strategy, said Ted Bailey, chief executive and founder of four-year-old Dataminr. The company is lately "making a lot" of headway with large hedge funds and government clients, he said.

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The roots of these computer programs go back to those built by media companies and hedge funds to trade around publicly disclosed information, such as earnings and economic data, say traders and programmers.

Media firms including Dow Jones, Bloomberg and Reuters began setting up "elementized news feeds" around 2006. With the feeds, this public information was piped nearly instantaneously to data centers and sold to trading firms. Dow Jones publishes The Wall Street Journal.

These trading firms would then devise computer programs to buy and sell based on an earnings report being up or down, or a firm being named in a lawsuit.

After a fake tweet sent markets swooning on Tuesday, so-called "tweet-scraping" and how financial firms use this information is under a spotlight. Telis Demos explains on digits. photo: twitter/AP.

Some of the new programs are rather simple, looking for key words in verified accounts of major news sources. Others use complex algorithms to detect patterns. Dataminr's program works by processing hundreds of millions of daily tweets instantly to find credible and actionable information that they can share with clients.

Dataminr looks at dozens of variables about each tweet, such as the influence of the user, the geo-location of where the tweet is sent from, and how tweets are clustered together.

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In 2010, Johan Bollen, an associate professor at Indiana University and two other professors published research showing how using Twitter could with more than 85% accuracy predict the daily up and down readings of the Dow.

Some investors that use news-scraping programs draw the line at Twitter, however. "The accuracy of tweets is a major concern," said Zeid Barakat, co-founder of Flyberry Capital, a startup that uses high-speed strategies to trade commodity futures around news events.

Credit Suisse AG doesn't use these sorts of algorithms because the technology is still developing, said Dan Mathisson, the head of U.S. equity trading.

Tuesday's incident "doesn't happen often enough to make it worthwhile" to invest in such technology, he said.

Others say being first is a critical advantage. Selerity Inc., based in Jersey City, N.J., detected an August 2012 tweet from a person who witnessed a fire at a Chevron Corp. refinery in Richmond, Calif., near San Francisco, news that hadn't reached the broader media, according to the firm's founder, Ryan Terpstra. The tweet read "oh [expletive] the chevron refinery in richmond [is] on fire!!!"

Selerity alerted clients, who were able to buy gasoline futures contracts before the news spread widely and caused prices to soar, says Mr. Terpstra.

In the case of Tuesday's commotion, Dataminr's computers not only flagged the event but the algorithms noticed quickly that there was no corroboration. Unlike the Boston Marathon bombing a week earlier, there were none of the telltale signs of a disaster: no sudden swell of tweets from people in the vicinity of the White House, for instance, Mr. Bailey said.

The company alerted customers to another tweet, from a reporter at the White House, saying the report appeared to be a false alarm. The AP and White House quickly issued official denials of the explosions shortly thereafter.

One of the first firms to embrace the small but growing industry being created around social media and investing was New York-based RavenPack.

The business, begun in 2007, now has dozens of hedge funds, mutual funds and large banks as clients, all of which have embraced social media more aggressively in the past year, said Armando Gonzalez, chief executive of the real-time news analysis firm. The company today counts several institutional investors with more than $5 billion in assets under management as clients of its social-media products.

When Tuesday's mini-crash happened, Mr. Gonzalez said he was inundated with questions from clients about how the incident could happen. Most wanted to be sure that RavenPack was using information only from trusted sources, which he said they had.

Mr. Gonzalez said he finished answering questions from clients at 2 a.m.

Corrections & Amplifications In an earlier version of this article, Ted Bailey of Dataminr was quoted as saying his firm was "making a lot of headwind" with clients. He says he misspoke and that he intended to convey that his firm was making "headway" with clients.

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